The 18 Top Use Cases of Artificial Intelligence in Banks - Fintech News

#artificialintelligence

This article in CustomerThink identifies many different solutions where Artificial Intelligence can enhance banking, but makes it appear these solutions are already widely deployed. While each solution is currently in-market by at least one large bank this is a far cry from broadly deployed. Mercator surveyed large banks and found 93 different Artificial Intelligence solutions deployed in 13 different departments. "Machines are getting smarter globally. Thanks to thriving Artificial Intelligence (AI) concept, companies can make their devices more powerful and'intelligent' to serve their customers in a better way. Both B2B and B2C businesses have started adopting this revolutionary technology as per their scale and size. However, the penetration of AI in the banking sector is somewhat limited to date. The distinct datasets and the risk of confidential data are primarily responsible for the sluggishness of AI integration in the banking system.


How AI-powered Mobile Banking App Enhances Customer Experience

#artificialintelligence

Machines are getting smarter globally. Thanks to thriving Artificial Intelligence (AI) concept, companies can make their devices more powerful and'intelligent' to serve their customers in a better way. Both B2B and B2C businesses have started adopting this revolutionary technology as per their scale and size. However, the penetration of AI in the banking sector is somewhat limited to date. The distinct datasets and the risk of confidential data are primarily responsible for the sluggishness of AI integration in the banking system.


AI in banks: risks and opportunities

#artificialintelligence

Swedish philosopher Nick Bostrom, in the book Superintelligence said, "Machine learning is the last invention that humanity will ever need to make." From electronic trading platforms to medical diagnosis, robot control, entertainment, education, health, and commerce, Artificial Intelligence (AI) and digital disruption have touched every field in the 21st century. AI has made its presence felt in all walks of life due to its ability to help the user innovate. It has also enabled users to make faster and more informed decisions with an increased amount of efficiency. Of late, the banking sector is becoming an active adapter of artificial intelligence--exploring and implementing this technology in new ways.


How is machine learning used in finance? – Machine Learning Perspectives – Medium

#artificialintelligence

From screening and approving loans to managing assets and preventing fraud, machine learning plays a crucial role on many levels in financial institutions. In this blog post, we'll explore some ways that machine learning improves business processes in the financial sector. Machine learning algorithms are far more effective for personalizing your customer experience than entire teams of employees. Simple demographics can't fully explain actual consumer behavior, so financial organizations should use machine learning to segment consumers by their level of sophistication and financial acumen, and then customize products and services accordingly. All relevant customer interaction data is used to train these algorithms, which then automatically builds statistical models that help correlate customers' preferences with their demographic, behavioral, and other characteristics.


Artificial Intelligence for the Banking Ecosystem Analytics Insight

#artificialintelligence

If there is one industry in which advanced technology has made a significant impact, it's the finance sector. For years, the finance sector has been dominated by traditional, 'legacy' banks. Who've built a reputation for long, slow and tedious processes. But with the introduction of digital banking and fintech, there has been a shift and many banks have embarked upon their digital transformation journeys. One of the main reasons for this shift is artificial intelligence.